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The Mexico SimSmoke tobacco control policy model: Development of a simulation model of daily and nondaily cigarette smoking

  • Luz María Sánchez-Romero,

    Roles Conceptualization, Writing – original draft

    Affiliation Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, United States of America

  • Luis Zavala-Arciniega,

    Roles Data curation, Formal analysis, Writing – review & editing

    Affiliations Tobacco Research Department, National Institute of Public Health, Cuernavaca, México, Department of Epidemiology, University of Michigan School Public Health, Ann Arbor, Michigan, United States of America

  • Luz Myriam Reynales-Shigematsu,

    Roles Conceptualization, Investigation, Writing – review & editing

    Affiliation Tobacco Research Department, National Institute of Public Health, Cuernavaca, México

  • Belén Sáenz de Miera-Juárez,

    Roles Writing – review & editing

    Affiliation Department of Economics, Autonomous University of Baja California Sur, La Paz, México

  • Zhe Yuan,

    Roles Data curation, Formal analysis

    Affiliation Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, United States of America

  • Yameng Li,

    Roles Formal analysis

    Affiliation Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, United States of America

  • Yan Kwan Lau,

    Roles Writing – review & editing

    Affiliation Department of Epidemiology, University of Michigan School Public Health, Ann Arbor, Michigan, United States of America

  • Nancy L. Fleischer,

    Roles Writing – review & editing

    Affiliation Department of Epidemiology, University of Michigan School Public Health, Ann Arbor, Michigan, United States of America

  • Rafael Meza,

    Roles Writing – review & editing

    Affiliation Department of Epidemiology, University of Michigan School Public Health, Ann Arbor, Michigan, United States of America

  • James F. Thrasher,

    Roles Investigation, Writing – review & editing

    Affiliations Tobacco Research Department, National Institute of Public Health, Cuernavaca, México, Department of Health Promotion, Education & Behavior, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America

  • David T. Levy

    Roles Conceptualization, Funding acquisition, Methodology, Writing – review & editing

    Affiliation Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, United States of America



Nondaily smoking has been on the rise, especially in Mexico. While Mexico has strengthened its tobacco control policies, their effects on nondaily smokers have gone largely unexamined. We developed a simulation model to estimate the impact of tobacco control policies on daily and nondaily smoking in Mexico.


A previously validated Mexico SimSmoke model that estimated overall trends in smoking prevalence from 2002 through 2013 was extended to 2018 and adapted to distinguish daily and nondaily smoking prevalence. The model was then validated using data from Mexican surveys through 2016. To gauge the potential effects of policies, we compared the trends in smoking under current policies with trends from policies kept at their 2002 levels.


Between 2002 and 2016, Mexico SimSmoke underestimated the reduction in male and female daily smoking rates. For nondaily smoking, SimSmoke predicted a decline among both males and females, while survey rates showed increasing rates in both genders, primarily among ages 15–44. Of the total reduction in smoking rates predicted by the model by 2018, tax policies account for more than 55%, followed by health warnings, cessation treatment, smoke-free air laws, and tobacco control spending.


Although Mexico SimSmoke did not successfully explain trends in daily and nondaily smoking, it helps to identify gaps in surveillance and policy evaluation for nondaily smokers. Future research should consider appropriate measures of nondaily smoking prevalence, trajectories between daily and nondaily smoking, and the separate impact of tobacco control policies on each group.


In 2004, Mexico ratified the World Health Organization Framework Convention on Tobacco Control (FCTC) treaty. Since then, Mexico has adopted stronger tobacco advertising restrictions, package health warnings and increased cigarette taxes [1]. Mexico’s prevalence of overall smoking has declined from 21.5% in 2007 to 19.0% in 2016. In particular, daily smoking prevalence decreased by 50% from 13.5% in 2002 to 7.0% in 2016. Meanwhile nondaily smoking prevalence increased by 35% from 8.8% in 2009 to 11.9% in 2016, comprising a large proportion of smokers in Mexico [2, 3]. This pattern of growth in the proportion of non-daily smokers is not only occurring in Mexico, but also in many middle-income countries, such as Brazil, India, Indonesia and Thailand [4], as well as in many high-income countries [5, 6].

Studies have suggested that the increase in nondaily smoking in Mexico is related to the increase in popularity of new tobacco products, particularly flavored capsule cigarettes [7], the increase in the sale of single cigarettes and multiproduct use in the population [7, 8], and the absence of cessation strategies targeted to nondaily smokers [9]. In addition, Mexico has implemented tobacco policies focused on daily cigarette smokers, which rarely consider nondaily and multiproduct use patterns [1, 10]. As nondaily smoking continues to grow and patterns of use continue to change (e.g., towards social users, infrequent and frequent nondaily users, and multiproduct users), it is important to evaluate the differential effect of current tobacco control policies on nondaily vs daily smokers.

To evaluate the potential effect of Mexico’s policies, the Mexico SimSmoke tobacco control simulation model was developed and validated through 2011. The model showed that overall smoking prevalence was reduced by 30% potentially due to policies implemented between 2002 and 2013 [11]. However, neither that model nor SimSmoke models developed for other countries have distinguished nondaily from daily smokers.

This study describes the update of the Mexico SimSmoke, to separately consider daily and nondaily smokers. This version builds upon the previously validated model [11, 12], extends policy level data to 2018 and estimates the potential role of implemented policies on daily and nondaily smoking prevalence.


Mexico SimSmoke is built upon separate population, smoking prevalence, smoking-attributable deaths, and policy modules. The model begins in 2002 to take advantage of the large-scale National Addictions Survey (ENA). ENA 2002 precedes the implementation of most major tobacco policies in Mexico. The model assumes a discrete-time, first-order Markov process to project future age and gender-specific population growth, smoking rates, and deaths from 2002 through 2060. Briefly, total population growth evolves through births, deaths, and migration. Smoking prevalence evolves through smoking initiation, cessation, and relapse, and changes in tobacco control policies.


Population, mortality, and migration data for 2002–2050 by single age (0 to 85+) and gender are from the Mexico National Council of Population (CONAPO) [13]. The population from birth to age 14 is classified as never smokers since minimal smoking occurs before that age [11, 12], and then evolves through mortality and net migration. Mexico SimSmoke predicts the population size by age group through 2018 within 5% of the CONAPO estimates.

Smoking prevalence

The baseline data for smoking prevalence are primarily from the 2002 National Addictions Survey (ENA) [14], a nationally representative multistage household survey of Mexicans aged 15 to 65. Current smokers are those who reported to have “ever smoked tobacco in their lifetime” and “had smoked in the past-30 days”. Current smokers were further classified as daily or nondaily smokers based on their answer to the question “Approximately, how many cigarettes have you smoked daily in the past 30-days?. Nondaily users are those who reported that they “do not smoke every day”. Former smokers are classified by the number of years quit. In the previous Mexico SimSmoke [11, 12], we limited the modeling exercise to established smokers, restricted to those who reported that they had smoked at least 100 cigarettes in their lifetime [3, 15]. However, because a large percentage of both daily and especially nondaily smokers, including older adults, reported that they have not smoked 100 cigarettes in their lifetime [3], we do not apply the 100-cigarette criterion for the current model. Instead, we conduct a sensitivity analysis applying that criterion.

Because ENA 2002 only contained population data through age 65, smoking prevalence data for those above age 65 was obtained from the 2000 National Health Survey (ENSA). The ENA 2000 estimates for ages 65 and above are adjusted by the relative difference in estimates for the age 45–64 age group between ENA and ENSA.

Baseline initiation rates at each age, after age 14, are calculated as the difference between the 2002 baseline smoking rate at each age and the smoking rate at the previous age. Initiation occurs from ages 14 through 28, based on the ages at which we observed increases in daily and nondaily smoking prevalence.

The cessation rate is calculated as the number of former smokers who quit during the last year divided by total smokers the previous year. Although estimated cessation rates were slightly higher for nondaily than daily smokers, we apply the same cessation rates to both groups, since nondaily smoker cessation rates may include a higher percentage of short-term quitters that are more likely to relapse. Due to a lack of suitable Mexican relapse rates in 2002, we used US rates [16] for both daily and nondaily smokers differentiated by quit years.

Tobacco control policies

Based on the World Health Organization MPOWER measures [17], SimSmoke evaluates the impact of cigarette excise taxes, smoke–free air laws, media campaigns, marketing bans, health warnings, cessation treatment policies, and youth access restriction. Although Mexico is an upper-middle-income country, we use the policy effects for high-income nations, because smoking trends indicate that Mexico is at later stages in the smoking epidemic.

Table 1 describes the policies and effect sizes. The effect sizes are applied as percentage reductions in smoking prevalence in the initial year and as reduced initiation and increased cessation rates in later years. Although effect sizes are based primarily on studies consisting mostly of daily smokers, the same policy effects are applied to daily and nondaily smokers. However, because nondaily smokers generally face less exposure to the impact of laws (e.g., due to less use), we conduct sensitivity analyses assuming half the policy effect sizes for nondaily smokers.

Table 1. Tobacco control policies, specifications and policy effect sizes*.

Mexico SimSmoke incorporates policy levels from 2002 to 2018, obtained from MPOWER Reports [17, 18], the Tobacco Control Report for the Region of the Americas 2013 and 2018 [19, 20], and communication with researchers from the Mexican National Institute of Public Health [1]. Mean annual real cigarette prices were obtained from the National Institute of Statistics and Geography (INEGI) [21].

Mexico had low-level smoke-free air laws for worksites except for health care and educational facilities from 2002 through 2007. In 2008, Mexico City and the state of Tabasco implemented laws for smoke-free workplaces, restaurants, and bars [12, 22]. Similar laws were adopted by other states since 2011. As a percent of the population, high-level worksite bans were 10% in 2008–2009, increasing to 18% in 2010–2011, and to 45% in 2014–2016. Restaurant and bar bans increased from 0% in 2002 to 60% for 2010–2012, and 70% from 2013 onwards. Based on the literature [17, 18, 23], the enforcement level is estimated at four on a ten-point scale for all years.

Before 2005, Mexico had limited tobacco control media campaigns. A national media campaign began in 2005, with a subsequent campaign in 2013 [10]. Mexico has a national tobacco control agency and in 2008 they reported a tobacco control expenditure of $0.00013 USD per capita for age 15+ [24], increasing to $0.08 USD in 2017 [25]. Tobacco control campaign levels increased from no campaign to a low-level campaign in 2005 [26] and remained at that level for all years.

Mexico had minimal restrictions on tobacco advertising in 2002. Advertising was banned for most hours on TV and radio in 2004 [26], and was expanded to all television and radio hours and billboards and some types of sponsorships in 2009 [27]. However, data from the 2009 Global Adult Tobacco Survey (GATS) and the National Survey of Drugs, Alcohol, and Tobacco Consumption (ENCODAT) indicated that more than 30% of the population still noticed retail advertisements [28, 29]. Advertising bans begin at a 50% low level in 2002–2003, increasing to 100% low-level in 2004 and to 75% moderate and 25% low-level in 2009, while enforcement is set at 5 out of 10 for all years [18, 29].

In 2002, health warnings covered a small portion of the pack (low-level). In 2004, they were increased to 50% of the package back (moderate-level) and then modified to 30% of the front with pictorial warnings and 100% of the back with only text warnings (high-level) in 2010 [30].

Cessation treatment policies consider the availability of treatment, including quit line and health care worker involvement. Nicotine replacement therapy was available without prescriptions from 2002 to 2018 [31]. From 2006 to 2012, a national program provided behavioral therapy, but with few referrals [12]. Cessation support has been partially covered in most primary care facilities, some hospitals, and communities since 2007 and has been available in some other places and offices since 2010. However, the use of pharmacotherapy as a cessation method decreased from 6.1% in 2009 to 3.5% in 2015 [32]. A quit line has been in place since 2008, but with minimal referrals [1], and is considered at a low level. Data from 2009 GATS [28] and 2016 ENCODAT [29] indicate that brief interventions were provided to about 25% of smokers with minimal advice to quit. We set the brief intervention index to a 20% level for all years.

Regarding youth access policies, Mexico has banned the sale of cigarettes to youth under age 18, but with minimal enforcement. According to the 2009 GATS, over 60% of youth were allowed cigarette purchase [33], and the 2016 ENCODAT [29] showed that 75% of adolescent smokers bought single cigarettes and 88% were not requested to show proof of age, which is considered low-level enforcement.

Model validation and projection

The model is validated by comparing predicted gender-specific daily and nondaily smoking prevalence rates from SimSmoke to estimates from five Mexican national representative surveys: 2011 ENA, 2012 National Health and Nutrition Survey (ENSANUT) [34], 2009 and 2015 GATS, and 2016 ENCODAT. Since 2009, Mexican national health surveys estimate the prevalence of daily and nondaily smoking based on the standardized question “Do you currently smoke tobacco on a daily basis, less than daily, or not at all?” Nondaily users are defined as those who answer, “less than daily”. We focus our validation on the 2016 ENCODAT, the most recent survey with the same design as the 2002 ENA. We further validate the model by age group.

To examine the potential policies’ effects on daily and nondaily smoking prevalence, we compare SimSmoke prevalence rates with policies implemented between 2002 and 2018 (status quo) to policies set at their 2002 level (counterfactual). To gauge the effect of each policy, we incorporate changes in the selected policy while holding other policies at their 2002 level. The impact of the policies is measured as the relative difference in prevalence between the status quo and counterfactual. Since SimSmoke policies effects are not additive, the role of an individual policy is measured relative to the summed effects of all individual policies.

Further details of the development and projections of the model are provided in a S1 Report.


Validation of current daily and nondaily smoking prevalence

Figs 1 and 2 present the daily and nondaily smoking prevalence projections by gender from SimSmoke and Mexico surveys using smoking estimates without the 100-cigarette lifetime criterion and assuming the same policy effects for nondaily and daily smokers.

Fig 1. Validation of daily smoking prevalence, ages 15–65 by gender, from Mexico SimSmoke and various national surveys,* 2002–2016.

*The survey point estimates (indicated by dots) and 95% confidence intervals were obtained from the National Addictions Survey (ENA) in 2002 and 2011, the Global Adult Tobacco Survey (GATS) in 2009 and 2015, the National Health and Nutrition Survey (ENSANUT) in 2012, and the National Survey of Drugs, Alcohol, and Tobacco Consumption (ENCODAT) in 2016.

Fig 2. Validation of nondaily smoking prevalence, ages 15–65 by gender, from Mexico SimSmoke and various national surveys*, 2002–2016.

*The survey point estimates (indicated by dots) and 95% confidence intervals were obtained from the National Addictions Survey (ENA) in 2002 and 2011, the Global Adult Tobacco Survey (GATS) in 2009 and 2015, the National Health and Nutrition Survey (ENSANUT) in 2012, and the National Survey of Drugs, Alcohol, and Tobacco Consumption (ENCODAT) in 2016.

For daily smoking prevalence ages 15–65, SimSmoke predicts a decline to 15.4% for males and 4.6% for females in 2016, compared to 11.0% and 3.3% respectively from ENCODAT. SimSmoke daily estimates for both genders, are above the survey’s upper limits of the 95% confidence interval (CI) but fall within the 95% CI for 2012. By age group (S2.1 Table in S1 Report), SimSmoke overestimates male daily smoking prevalence (especially for ages 25–44), except for ages 15–44 in 2012, and overestimates female daily smoking rates for all age groups (especially for ages 15–24) for all surveys except for ages 25–65 in 2012.

For male nondaily smoking prevalence ages 15–65 in 2016, SimSmoke predicts a decline for males to 8.6% compared to an increase to 18.4% from ENCODAT and a decline for females to 3.2% compared to an increase to 6.0% from ENCODAT. Nondaily SimSmoke predictions are below the 95% CIs of all survey estimates, except for females from the 2009 GATS. For ages 18–24 and 25–64, SimSmoke nondaily smoking predictions for both genders are below all survey 95% CIs, except for females ages 25–44 in 2009. The model predicts better for ages 45–65 but still underestimates nondaily prevalence for males in 2016.

The potential effect of tobacco control policies implemented through 2018

Table 2 shows the results for daily and nondaily smoking prevalence comparing the status-quo scenario (with actual policies) to the counterfactual (no new policies implemented after 2002).

Table 2. Current smoking prevalence by smoking status and gender, from Mexico SimSmoke under different policy scenarios, 2002–2060.

Under the status quo, SimSmoke projects daily smoking prevalence in 2018 at 14.6% for males and 4.4% for females and nondaily at 8.2% for males and 3.0% for females. Compared to the counterfactual, the SimSmoke status-quo projects that the daily smoking prevalence in 2018 is reduced, in relative terms, by 25.6% for male and 26.7% for females, and that the nondaily smoking prevalence is reduced by 26.9% for males and 27.3% for females.

By individual policy for the year 2018, cigarette price increases are projected to reduce daily smoking rates by 14.4% for males and 15.5% for females and to reduce nondaily rates by 16.0% for males and 16.1% for females. Smoke-free air laws yield relative reductions of 2.7% for male and 2.8% for female daily smokers and relative reductions of 3.2% for males and 3.4% for females for nondaily smokers. Other policies yield similar estimated effects for both genders and daily and nondaily smokers: 4.1% for health warnings, 2.1% for cessation treatment policies, 1.7% for marketing restrictions, and 1.1% for tobacco control campaigns. As a percent of the total reduction in daily and nondaily rates due to policies, SimSmoke attributes 56% to increased cigarette prices, 15% to health warnings, 11% to smoke-free air laws, 8% to cessation treatments, 6% to marketing restrictions, and 4% to tobacco control mass media campaigns.

Sensitivity analyses

To further validate Mexico SimSmoke projections of daily and nondaily smoking, we perform two sensitivity analyses, one assuming half of the original policy effect sizes for nondaily smokers and a second one assuming half of the original effect combined with using the100-cigarettes lifetime screen for defining current smoking prevalence (S1 Report). Assuming half of the original effect, daily smoking projections are unaffected, but SimSmoke nondaily smoking projections in 2016 are closer to those observed with full policy effects, but still below survey estimates (model: 10% vs. survey: 18.4% for males; model: 3.8% vs. survey: 6.0% for females) (S2.2 Table in S1 Report). The relative reduction in smoking prevalence from all policies compared to the no policy counterfactual is reduced from about 22% to 17% for nondaily smokers (S3.2 Table in S1 Report).

Using the 100-cigarettes lifetime screen for defining current smoking prevalence in combination with half of the policy effect, the relative prediction errors for daily smokers are roughly the same compared to analyses without the screen. Applying the assumption of half the policy effects for nondaily as daily smokers and using the prevalence estimates with the 100 cigarettes lifetime screen, the relative underestimation of nondaily smoking from the model is still large for nondaily smokers by 2016 (model: 5.2% vs. survey: 12.3% for males; model: 1.4% vs. survey: 3.6% for females) (S2.4 Table in S1 Report) In that case, the relative reduction due to policies is still about 17% (S3.4 Table in S1 Report).


Previous SimSmoke models, including the earlier Mexico model [11, 3538], have generally validated well against country-specific smoking prevalence. However, the updated Mexico SimSmoke does not validate well against population trends, even after distinguishing daily and nondaily smokers. By 2016, SimSmoke underpredicts the reduction in daily smoking compared to survey estimates. SimSmoke also predicts a decline in nondaily smoking rates, but surveys show an increasing trend.

While simulation models are generally evaluated in terms of their ability to predict actual behavior, the failure of this model to predict well suggests areas for future research. In particular, the poor validation of the model points toward the need for a better understanding of nondaily relative to daily smoking. One potential cause for poor predictions may be related to the use of the 100-cigarettes lifetime screen. However, applying the screen did not improve model validation for nondaily smokers. A recent study [3] observed that Mexico’s nondaily smoking prevalence without the 100-cigarettes screen for ages 15–24 was nearly 70% greater than with the screen, and differences were observed even among older age groups. Similar variations using the 100-cigarettes screen have been observed in a US study [39].

Attention should also be directed at the impact of policies on daily and nondaily smokers. Mexico SimSmoke predicts more than a 35% reduction in smoking potentially due to policies implemented up to 2018. However, with the reductions understated for daily smokers and overstated for nondaily smokers, the results should be interpreted with caution. While the model predictions improve slightly by assuming half the effect of policies on nondaily compared to daily smokers, SimSmoke still fails to predict the observed increase in nondaily smoking. Indeed, when combining daily and nondaily smokers, Mexico SimSmoke still overpredicts the reductions between 2002 to 2016 in overall smoking prevalence relative to surveys (males: 26% model vs. 13% survey, females: 27% model vs. 18% survey).

While the effects of policies projected by Mexico SimSmoke are likely biased towards daily users, the results still highlight the potential beneficial effect of different policies. Price increases are projected to have the greatest effect on smoking. However, increased cigarette taxes may have led to reductions in the number of days smoked, i.e., substitution of daily for nondaily smoking, as well as a reduced effect on nondaily smokers. A previous study [40] found that 62.1% of Mexican nondaily and 25.9% of daily smokers purchased single cigarettes and paying more than double compared with those purchasing cigarette packs, suggesting that nondaily smokers purchasing single cigarettes may be less responsive to price. Smoke-free air law policies may also have a weaker effect on nondaily users, with nondaily smokers deciding to smoke only on weekends and to avoid smoke-free restaurants and bars.

Cessation treatment policies, such as health care provider brief interventions, may also have less impact on nondaily than daily smokers. Traditionally, nondaily smokers are frequently considered as low nicotine dependent users and assumed to have less incentive to quit. As a result, health personnel are less likely to advise cessation [5]. However, evidence has shown that nondaily smokers may have a similar or greater physical and psychological dependency and lower intentions to quit than daily cigarette users [9, 41, 42]. Nondaily smokers also perceive lower health risks than daily smokers [42, 43], suggesting that media campaigns and cigarette pack warnings may have a limited effect on this group. To address these issues, media campaigns and cessation treatment may need to employ strategies that are tailored to reach nondaily smokers.

SimSmoke models are generally used to calculate smoking attributable deaths and long-term projections. If policies remain at 2018 levels, Mexico SimSmoke projects a reduction in the prevalence of nondaily smoking of 38% by 2060 (8.2% to 5.8% for males and 3.0% to 2.1% for females from 2018 to 2060) with a similar reduction in prevalence for daily smokers (14.6% vs. 10.8% for males and from 4.4% to 2.7% for female) (S3.1 Table in S1 Report) and 1,186,165 fewer deaths occurring from 2018 to 2060 from which 14% will be from nondaily users (S4.1 Table in S1 Report). Due to the poor predictability of the model, these results may be underestimating the impact of nondaily users in the burden of smoking in Mexico; however, they emphasize the differential effect of the control policies between daily and nondaily users.

Results from our simulation model depend on the data, input parameters, and assumptions underlying the model. The model’s failure to predict the increasing patterns of nondaily usage may reflect the Mexico SimSmoke model’s limitations. Daily and nondaily smoking prevalence estimates were obtained from ENA 2002, but it was not until after GATS 2009 that the Mexican national health surveys started to use a standardized measure to collect nondaily prevalence (i.e., “Do you currently smoke tobacco on a daily basis, less than daily, or not at all?”). Differences in the definition of nondaily users between the data used for model input and validation may contribute to the failure in our validation. Another limitation is that projections are based on the cessation rates used in the model. While we assume the same quit rates for both, recent studies found higher quit rates among nondaily than daily [44], as might be expected due to reduced nicotine intake. However, higher quit rates would have led to an even greater decline in nondaily smoking than our projections rather than the observed increase by surveys. Furthermore, nondaily users’ cessation behaviors are variable [45] and more study is warranted on the quitting and switching patterns of daily and nondaily smokers. In addition, the policy effects for nondaily smokers used in this modeling exercise are tentative. We apply sensitivity analyses by reducing the effect of some policies in order to reflect potentially lower policies impacts on nondaily smokers, but further ranges should be explored.

Another limitation of our model that could be a source of discrepancy between model projections and observed behavior may be the failure to consider the evolution of nicotine delivery products. The rapid uptake of new nicotine delivery products may have influenced tobacco use patterns in such a way as to undermine cigarette-oriented tobacco control policies. For instance, cigarettes with flavor capsules have rapidly gained market share in countries like Mexico [46], where they were introduced soon after the General Tobacco Control Law was implemented. Furthermore, despite a ban on e-cigarette sales in Mexico, e-cigarette use has rapidly grown, particularly amongst youth and adult smokers [47]. However, trends toward increased nondaily smoking began before e-cigarettes were introduced.

Better information is needed to understand the trajectories and differential effects of implemented policies on daily and nondaily smokers. Our study casts light on the shortage of surveillance and policy evaluation data regarding nondaily smokers’ behaviors. With tobacco usage behaviors becoming more complex, the lack of nondaily data and understanding represents a barrier to effectively regulating these products. The World Health Organization [48] and the Institute of Health Metrics and Evaluation [49] have focused on overall current or daily smokers, and often do not report nondaily smoking. The reporting of nondaily smokers’ prevalence by leading international agencies would encourage countries to follow their lead. There already exist standardized tools to monitor nondaily tobacco use. The Global Tobacco Surveillance System (GTSS) collects data on tobacco surveillance through four different surveys and effectively reports nondaily (occasional) data for 22 countries. As part of the GTSS, GATS provides a subset of standardized tobacco monitoring measures that can assist other countries in collecting data on smoking prevalence and tobacco control policies indicators. Systematizing the use of this set of questions in national surveys would be an important first step towards improving surveillance [50]. Further, to better capture nondaily trends and users’ characteristics, the nondaily use definition could be expanded beyond reporting “occasional use” or “consumption in one or more days in the past 30 days” by including frequency and intensity measures.

While the heterogeneity and stability of nondaily users (e.g., frequent and infrequent, exclusive, or multiproduct users) behaviors makes it difficult to estimate the effect of a policy on this group, it is important to characterize the response of nondaily users to regulations and apply these characterizations to future tobacco control policies development [51]. This need is particularly relevant for the Mexican and other Hispanic/Latino populations which have shown a higher prevalence of nondaily use than other populations [5254], and especially for Mexicans who are more likely to be nondaily smokers than other Hispanic/Latino individuals [55]. Although this behavior may in part be attributed to social influence, it has also been observed that the presence of a gene variation in Hispanic/Latino smokers has potential influence in their predisposition towards low intensity nondaily use [56].

As one of the countries with the highest proportion of nondaily smokers, Mexico’s particular tobacco prevalence and control panorama calls attention to the relevance of including nondaily monitoring indicators as part of the policy evaluations. Nondaily smokers are an important contributor to the tobacco-associated disease burden [57]. Mexico’s overall tobacco prevalence has remained stable since 2009 (around 80%) with a reduction in prevalence from daily smokers (from 8.6% to 7.5% in 2016 [2]. However, Mexico’s smoking-attributable deaths have increased from 51.6 thousand in 2017 (7.5% of total deaths) to 58.2 thousand in 2019 (8.1% of total deaths) [58] due to the increase in nondaily prevalence. Other countries have started to show similar tobacco trends [59]. Brazil, a high-achieving tobacco control country, has seen a reduction in the rate of decline in smoking prevalence [60, 61], with an increase in nondaily and in illicit cigarette use [62], similar to the conditions in Mexico which have contributed to the rise in nondaily use. Mexico’s lack of surveillance of nondaily use combined with the low enforcement of implemented policies also characterizes other low and middle-income countries [63]. Public health researchers need to consider systematizing the collection of the nondaily smoking data to monitor and prevent future scenarios like the one observed from Mexico.

Addressing the needed improvements in surveillance also goes hand-in-hand with efforts to reassess and update tobacco control regulations. Fifteen years ago, Mexico was one of the first countries in America to ratify the WHO-FCTC treaty. Since then no major changes to the policies have been made [1]. Despite the lack of major policy changes, previously implemented policies were reducing the smoking problem in Mexico, as observed by the validation of our previous Mexico SimSmoke models [11, 12]. However, with the changes in population smoking patterns in recent years, the implemented policies appear to no longer address Mexico’s population smoking patterns and needs. By not moving forward, there is the risk of losing the reduction in smoking prevalence and the requisite public health benefits that have been obtained in previous years [3, 64].

Despite a failure to capture actual trends, Mexico SimSmoke helps identify gaps in surveillance and policy evaluation. Nondaily use has become an important public health problem. The results presented here demonstrate a need to better capture the dynamic relationship between daily and nondaily smoking and how policies affect these two groups. Mexico’s nondaily smoking has increased, and future policy will need to better target nondaily smokers. More generally, nondaily smoking is common in many countries, and further advances in tobacco control will require a better understanding of this group’s characteristics.


  1. 1. Reynales-Shigematsu LM, Wipfli H, Samet J, Regalado-Pineda J, Hernandez-Avila M. Tobacco control in Mexico: a decade of progress and challenges. Salud Publica Mex. 2019;61(3):292–302. pmid:31276348
  2. 2. Zavala-Arciniega L, Reynales-Shigematsu LM, Levy DT, Lau YK, Meza R, Gutierrez-Torres DS, et al. Smoking trends in Mexico, 2002–2016: before and after the ratification of the WHO’s Framework Convention on Tobacco Control. Tob Control. 2020.
  3. 3. Levy D, Zavala-Arciniega L, Reynales-Shigematsu L, Fleischer N, Yuan Z, Li Y, et al. Measuring smoking prevalence in a middle income nation: An examination of the 100 cigarettes lifetime screen. Global Epidemiology. 2019;1. pmid:33907731
  4. 4. World Health Organization. The GATS Atlas: Global Adult Tobacco Survey 2019 [updated January 23, 2019.
  5. 5. Kotz D, Fidler J, West R. Very low rate and light smokers: smoking patterns and cessation-related behaviour in England, 2006–11. Addiction. 2012;107(5):995–1002. pmid:22126678
  6. 6. Schauer GL, Malarcher AM, Mowery P. National Trends in Frequency and Amount of Nondaily Smoking, and Relation to Quit Attempts, 2000–2012. Nicotine Tob Res. 2016;18(6):1539–44. pmid:26588937
  7. 7. Zavala-Arciniega L, Gutierrez-Torres DS, Reynales-Shigematsu LM, Barrientos-Gutierrez I, Fleischer NL, Meza R, et al. Prevalence, proportion and correlates of flavor capsule cigarette use in Mexico: results from the National Health and Nutrition Survey (ENSANUT) 2018–19. Salud Publica Mex. 2020;Revision.
  8. 8. Zavala-Arciniega L. Tobacco use and tobacco control policies in Mexico. A secondary analyses of the Global Adult Tobacco Survey (GATS 2009–2015). Society For Research On Nicotine and Tobacco, 26th Annual Meeting; New Orleans, Louisiana2020.
  9. 9. Paz-Ballesteros WC, Zavala-Arciniega L, Gutierrez-Torres DS, Ponciano-Rodriguez G, Reynales-Shigematsu LM. [Evaluation of physical and psychological dependence in Mexican adult smokers, Encodat 2016.]. Salud Publica Mex. 2019;61(2):136–46. pmid:30958956
  10. 10. IHME. The Importance of Tobacco Control in Mexico.: Institute of Health Metrics and Evaluation; 2019 [
  11. 11. Fleischer NL, Thrasher JF, Reynales-Shigematsu LM, Cummings KM, Meza R, Zhang Y, et al. Mexico SimSmoke: how changes in tobacco control policies would impact smoking prevalence and smoking attributable deaths in Mexico. Glob Public Health. 2017;12(7):830–45. pmid:26837721
  12. 12. Reynales-Shigematsu LM, Fleischer NL, Thrasher JF, Zhang Y, Meza R, Cummings KM, et al. Effects of tobacco control policies on smoking prevalence and tobacco-attributable deaths in Mexico: the SimSmoke model. Rev Panam Salud Publica. 2015;38(4):316–25. pmid:26758223
  13. 13. CONAPO. Consejo Nacional de Populacion Mexico City, Mexico2019 [
  14. 14. Kuri-Morales PA, Gonzalez-Roldan JF, Hoy MJ, Cortes-Ramirez M. [Epidemiology of tobacco use in Mexico]. Salud Publica Mex. 2006;48 Suppl 1:S91–8. pmid:17684694
  15. 15. Bondy SJ, Victor JC, Diemert LM. Origin and use of the 100 cigarette criterion in tobacco surveys. Tob Control. 2009;18(4):317–23. pmid:19491091
  16. 16. Hughes JR, Keely J, Naud S. Shape of the relapse curve and long-term abstinence among untreated smokers. Addiction. 2004;99(1):29–38. pmid:14678060
  17. 17. World Health Organization. WHO Report on the Global Tobacco Epidemic, 2008: The MPOWER package. Geneva; 2008.
  18. 18. WHO. WHO Report on the Global Tobacco Epidemic, 2013. Enforcing bans on tobacco advertising, promotion and sponsorship. Geneva, Switzerland: World Health Organization; 2013.
  19. 19. Organization Panamericana de la Salud. Informe sobre Control del Tabaco para la Región de las Américas. Washington, DC: OPS/OMS; 2013.
  20. 20. Pan American Health Organization. Report on Tobacco Control in the Region of the Americas, 2018. Washington, D.C.: PAHO; 2018.
  21. 21. National Institute of Statistics and Geography (INEGI). Consulta de Precios Promedio 2019 [cited 2020 January].
  22. 22. Thrasher JF, Perez-Hernandez R, Swayampakala K, Arillo-Santillan E, Bottai M. Policy support, norms, and secondhand smoke exposure before and after implementation of a comprehensive smoke-free law in Mexico city. Am J Public Health. 2010;100(9):1789–98. pmid:20466952
  23. 23. Zavala-Arciniega L, Gutiérrez-Torres D, Paz-Ballesteros W, Reynales-Shigematsu L, Fleischer N. Leyes de Ambientes Libres de Humo de Tabaco y Factores asociados a la Exposición al Humo de Tabaco. México 2016. Salud Publica de México. 2018;under review.
  24. 24. World Health Organization. WHO report on the global tobacco epidemic, 2009: implementing smoke-free environments. MPOWER. WHO Press., editor. Geneva, Switzerland 2009.
  25. 25. World Health Organization. WHO report on the global tobacco epidemic, 2017: Monitoring tobacco use and prevention policies. MPOWER. WHO Press., editor. Geneva, Switzerland 2017.
  26. 26. Ramirez-Barba EJ, Saro-Boardman E, Vazquez-Guerrero A, Vazquez-Guerrero MA. [The General Law on Smoking Control in Mexico]. Salud Publica Mex. 2008;50 Suppl 3:S372–83.
  27. 27. Perez-Hernandez R, Thrasher JF, Rodriguez-Bolanos R, Barrientos-Gutierrez I, Ibanez-Hernandez NA. [Tobacco advertising and promotions: changes in reported exposure in a cohort of Mexican smokers]. Salud Publica Mex. 2012;54(3):204–12. pmid:22689158
  28. 28. Centers for Disease Control and Prevention (CDC), Global Tobacco Surveillance System, National Council Against Addictions (Mexico), National Institute of Public Health (Mexico), Pan American Health Organization (PAHO), Secretariat of Health (Mexico), WHO Framework Convention on Tobacco Control. Mexico Global Adult Tobacco Survey 2009.
  29. 29. Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz; Instituto Nacional de Salud Pública CNClA, Secretaría de Salud,. Encuesta Nacional de Consumo de Drogas, Alcohol y Tabaco 2016–2017: Reporte de Tabaco Ciudad de México, México: INPRFM; 2017 [
  30. 30. Thrasher JF, Perez-Hernandez R, Arillo-Santillan E, Barrientos-Gutierrez I. [Towards informed tobacco consumption in Mexico: effect of pictorial warning labels in smokers]. Salud Publica Mex. 2012;54(3):242–53. pmid:22689162
  31. 31. World Health Organization. WHO report on the global tobacco epidemic, 2019. Country Profile: Mexico. Geneva, Switzerland: WHO; 2019.
  32. 32. CDC Foundation, Government of Mexico, National Institute of Public Health (Mexico), Secretariat of Health (Mexico). Mexico Global Adult Tobacco Survey 2015.
  33. 33. Centers for Disease Control. Mexico Global Youth Tobacco Survey 2018 [
  34. 34. Gutiérrez JP, Rivera-Dommarco J, Shamah-Levy T, Villalpando-Hernández S, Franco A, Cuevas-Nasu L, et al. Encuesta Nacional de Salud y Nutrición 2012. Resultados Nacionales. Cuernavaca, México: Instituto Nacional de Salud Pública; 2012.
  35. 35. Levy DT, Cho SI, Kim YM, Park S, Suh MK, Kam S. SimSmoke model evaluation of the effect of tobacco control policies in Korea: the unknown success story. Am J Public Health. 2010;100(7):1267–73. pmid:20466968
  36. 36. Levy D, de Almeida LM, Szklo A. The Brazil SimSmoke policy simulation model: the effect of strong tobacco control policies on smoking prevalence and smoking-attributable deaths in a middle income nation. PLoS Med. 2012;9(11):e1001336. pmid:23139643
  37. 37. Levy D, Rodriguez-Buno RL, Hu TW, Moran AE. The potential effects of tobacco control in China: projections from the China SimSmoke simulation model. BMJ. 2014;348:g1134. pmid:24550245
  38. 38. Levy DT, Benjakul S, Ross H, Ritthiphakdee B. The role of tobacco control policies in reducing smoking and deaths in a middle income nation: results from the Thailand SimSmoke simulation model. Tob Control. 2008;17(1):53–9. pmid:18218810
  39. 39. Ryan H, Trosclair A, Gfroerer J. Adult current smoking: differences in definitions and prevalence estimates—NHIS and NSDUH, 2008. J Environ Public Health. 2012;2012:918368. pmid:22649464
  40. 40. Hall MG, Fleischer NL, Reynales-Shigematsu LM, Arillo-Santillan E, Thrasher JF. Increasing availability and consumption of single cigarettes: trends and implications for smoking cessation from the ITC Mexico Survey. Tob Control. 2015;24 Suppl 3:iii64–iii70. pmid:25192772
  41. 41. Tindle HA, Shiffman S. Smoking cessation behavior among intermittent smokers versus daily smokers. Am J Public Health. 2011;101(7):e1–3. pmid:21566030
  42. 42. Berg CJ, Schauer GL, Buchanan TS, Sterling K, DeSisto C, Pinsker EA, et al. Perceptions of addiction, attempts to quit, and successful quitting in nondaily and daily smokers. Psychol Addict Behav. 2013;27(4):1059–67. pmid:24364689
  43. 43. Cooper TV, Taylor T, Murray A, DeBon MW, Vander Weg MW, Klesges RC, et al. Differences between intermittent and light daily smokers in a population of U.S. military recruits. Nicotine Tob Res. 2010;12(5):465–73. pmid:20203108
  44. 44. Swayampakala K, Thrasher J, Carpenter MJ, Shigematsu LM, Cupertio AP, Berg CJ. Level of cigarette consumption and quit behavior in a population of low-intensity smokers—longitudinal results from the International Tobacco Control (ITC) survey in Mexico. Addict Behav. 2013;38(4):1958–65. pmid:23380491
  45. 45. Schauer GL, Malarcher AM, Berg CJ. Differences in smoking and cessation characteristics among adult nondaily smokers in the United States: findings from the 2009–2010 National Adult Tobacco Survey. Nicotine Tob Res. 2014;16(1):58–68. pmid:23925825
  46. 46. Thrasher JF, Islam F, Barnoya J, Mejia R, Valenzuela MT, Chaloupka FJ. Market share for flavour capsule cigarettes is quickly growing, especially in Latin America. Tob Control. 2017;26(4):468–70. pmid:27329114
  47. 47. Zavala-Arciniega L, Reynales-Shigematsu LM, Lozano P, Rodriguez-Andrade MA, Arillo-Santillan E, Thrasher JF. Patterns of awareness and use of electronic cigarettes in Mexico, a middle-income country that bans them: Results from a 2016 national survey. Prev Med. 2018;116:211–8. pmid:30261244
  48. 48. WHO global report on trends in prevalence of tobacco use 2000–2025, third edition. Geneva: World Health Organization; 2019.
  49. 49. Collaborators GBDT. Smoking prevalence and attributable disease burden in 195 countries and territories, 1990–2015: a systematic analysis from the Global Burden of Disease Study 2015. Lancet. 2017;389(10082):1885–906. pmid:28390697
  50. 50. Global Adult Tobacco Survey Collaborative Group. Tobacco Questions for Surveys: A Subset of Key Questions from the Global Adult Tobacco Survey (GATS). Atlanta, GA.,: Center for Disease Control and Prevention; 2011.
  51. 51. Pacek LR, Wiley JL, McClernon FJ. A Conceptual Framework for Understanding Multiple Tobacco Product Use and the Impact of Regulatory Action. Nicotine Tob Res. 2019;21(3):268–77. pmid:29931176
  52. 52. Trinidad DR, Perez-Stable EJ, Emery SL, White MM, Grana RA, Messer KS. Intermittent and light daily smoking across racial/ethnic groups in the United States. Nicotine Tob Res. 2009;11(2):203–10. pmid:19246433
  53. 53. Sakuma KK, Felicitas-Perkins JQ, Blanco L, Fagan P, Perez-Stable EJ, Pulvers K, et al. Tobacco use disparities by racial/ethnic groups: California compared to the United States. Prev Med. 2016;91:224–32. pmid:27575315
  54. 54. Reyes-Guzman CM, Pfeiffer RM, Lubin J, Freedman ND, Cleary SD, Levine PH, et al. Determinants of Light and Intermittent Smoking in the United States: Results from Three Pooled National Health Surveys. Cancer Epidemiol Biomarkers Prev. 2017;26(2):228–39. pmid:27760782
  55. 55. Kaplan RC, Bangdiwala SI, Barnhart JM, Castaneda SF, Gellman MD, Lee DJ, et al. Smoking among U.S. Hispanic/Latino adults: the Hispanic community health study/study of Latinos. Am J Prev Med. 2014;46(5):496–506. pmid:24745640
  56. 56. Saccone NL, Emery LS, Sofer T, Gogarten SM, Becker DM, Bottinger EP, et al. Genome-Wide Association Study of Heavy Smoking and Daily/Nondaily Smoking in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Nicotine Tob Res. 2018;20(4):448–57. pmid:28520984
  57. 57. Inoue-Choi M, Shiels MS, McNeel TS, Graubard BI, Hatsukami D, Freedman ND. Contemporary Associations of Exclusive Cigarette, Cigar, Pipe, and Smokeless Tobacco Use With Overall and Cause-Specific Mortality in the United States. JNCI Cancer Spectr. 2019;3(3):pkz036. pmid:31321380
  58. 58. Institue of Health Metrics and Evaluation. GBD Compare Vizhub. 2019 [cited 2020 November 2020].
  59. 59. Centers for Disease Control and Prevention. National Center for Chronic Disease Prevention and Health Promotion, Office of Smoking and Health, [cited 2020 14, November].
  60. 60. Malta DC, Flor LS, Machado IE, Felisbino-Mendes MS, Brant LCC, Ribeiro ALP, et al. Trends in prevalence and mortality burden attributable to smoking, Brazil and federated units, 1990 and 2017. Popul Health Metr. 2020;18(Suppl 1):24. pmid:32993660
  61. 61. Global Tobacco Surveillance System Data (GTSSData).
  62. 62. Szklo A, Iglesias RM, Carvalho de Souza M, Szklo M, Maria de Almeida L. Trends in Illicit Cigarette Use in Brazil Estimated From Legal Sales, 2012–2016. Am J Public Health. 2018;108(2):265–9. pmid:29267067
  63. 63. Chow CK, Corsi DJ, Gilmore AB, Kruger A, Igumbor E, Chifamba J, et al. Tobacco control environment: cross-sectional survey of policy implementation, social unacceptability, knowledge of tobacco health harms and relationship to quit ratio in 17 low-income, middle-income and high-income countries. BMJ Open. 2017;7(3):e013817. pmid:28363924
  64. 64. Ng M, Freeman MK, Fleming TD, Robinson M, Dwyer-Lindgren L, Thomson B, et al. Smoking prevalence and cigarette consumption in 187 countries, 1980–2012. JAMA. 2014;311(2):183–92. pmid:24399557